AUTHOR=Al-Haddad Alaa , Alrabadi Mikel , Saadeh Othman , Alrabadi George , Hassona Yazan 

TITLE=The evaluation of tooth whitening from a perspective of artificial intelligence: a comparative analytical study

JOURNAL=Frontiers in Digital Health

VOLUME=Volume 7 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2025.1710159

DOI=10.3389/fdgth.2025.1710159

ISSN=2673-253X

ABSTRACT=BackgroundArtificial intelligence (AI) chatbots are increasingly consulted for dental aesthetics information. This study evaluated the performance of multiple large language models (LLMs) in answering patient questions about tooth whitening.Methods109 patient-derived questions, categorized into five clinical domains, were submitted to four LLMs: ChatGPT-4o, Google Gemini, DeepSeek R1, and DentalGPT. Two calibrated specialists evaluated responses for usefulness, quality (Global Quality Scale), reliability (CLEAR tool), and readability (Flesch-Kincaid Reading Ease, SMOG index).ResultsThe models generated consistently high-quality information. Most responses (68%) were “very useful” (mean score: 1.24 ± 0.3). Quality (mean GQS: 3.9 ± 2.0) and reliability (mean CLEAR: 22.5 ± 2.4) were high, with no significant differences between models or domains (p > 0.05). However, readability was a major limitation, with a mean FRE score of 36.3 (“difficult” level) and a SMOG index of 11.0, requiring a high school reading level.ConclusionsContemporary LLMs provide useful and reliable information on tooth whitening but deliver it at a reading level incompatible with average patient health literacy. To be effective patient education adjuncts, future AI development must prioritize readability simplification alongside informational accuracy.